A method of classification twitter posting location for a specific space

Research output: Contribution to journalConference articlepeer-review

Abstract

Under the definition of Baseball Stadium as a specific space, locations from which tweets relating to relevant spaces had been posted were classified whether inside or outside the specific space. As the classification method, BERT being one of the natural language processing models was employed. Through the comparison between the features of tweets inside and outside a specific space, it was revealed that there were differences between them in terms the number of URLs and media including photographs provided in them and shown that classification accuracy would improve by combining the numbers of URLs and media provided in tweets and their contents. In addition, through the extraction and comparison of words affecting the results of classification using LIME, what types of words and information had impacts on the judgement of classification were visualized.

Original languageEnglish
Pages (from-to)2365-2374
Number of pages10
JournalProcedia Computer Science
Volume192
DOIs
StatePublished - 2021
Event25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021 - Szczecin, Poland
Duration: 8 Sep 202110 Sep 2021

Keywords

  • BERT
  • Classification
  • LIME
  • Machine learning
  • NLP
  • Social sensor
  • Text mining
  • Twitter

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